As online learning platforms become prevalent, online learning has been an important way for college students. Online learning engagement, as an evaluation of online learning quality, is crucial for enhancing learning quality and promoting higher education by investigating college students’ engagement and its influencing factors in the online learning environment. This paper aims to identify key factors affecting college students’ online learning behavioral engagement. Based on a literature review, the Delphi expert consultation method was used to build an assessment framework covering five dimensions (participation, concentration, interaction, challenge, and self-monitoring) with sixteen specific indicators. The Analytic Hierarchy Process (AHP) determined the weights of these factors. Then, data from 63 students using the “Ketangpai” online learning platform were collected and analyzed to explore the correlation and predictive relationships between online learning behavior indicators and academic achievements. The results showed a strong correlation between the frequency of accessing online learning resources and long-term online learning and academic performance, and a prediction model was established. The framework offers theoretical and methodological insights for designing online learning activities and evaluating learning quality. It supports intervening in and assessing college students’ online learning processes and improving learning quality. Also, exploring the relationship helps educators formulate personalized online teaching strategies, improving online education effectiveness and students’ learning experiences.

As a technology-enhanced student-centered learning environment, smart classrooms are becoming increasingly popular in higher education. It is undoubtedly important to understand how seating and motivational factors affect situational engagement and satisfaction in smart classrooms. Pre-survey, experience sampling method, and post-survey were used in this study to conduct a longitudinal survey of 113 pre-service teachers in three courses at a university in central China. Descriptive statistics, bivariate correlations, hierarchical linear modeling, and hierarchical linear regression were used to investigate the effects of seating factors and motivational factors on engagement and satisfaction in smart classrooms. We found: (1) for the seating factor, the distance of the seat from the center point predicted student situational engagement in the smart classroom; (2) for motivational factors, needs of competence and competence during the activity predicted student situational engagement, while autonomous motivation at the beginning of a course strongly predicted student situational engagement in subsequent activities; and (3) of all the factors, situational engagement was a significant predictor of students’ final course satisfaction and fully mediated the relationship between autonomous motivation and satisfaction. Finally, some practice implications are discussed to improve engagement and satisfaction in technology-enhanced environments.